Skin blister biopsies allows a "bird's eye" view of the spatial pattern of epidermal nerve fibers (ENFs) across the epidermis. Visual comparison of blister images from diabetic and nondiabetic subjects shows the spatial pattern of ENFs becomes more "clustered" as neuropathy advances. Accurate quantification of these observations via spatial statistics would provide both a minimally invasive screening technique, and a tool to assess other proposed biomarkers of early neuropathy. We propose a focused two year research program (R21) to assess the accuracy and reliability of the use of spatial statistics to quantify observed spatial patterns of ENFs in blister images. We will: 1. Calculate intra- and interindividual variation for measures of spatial clustering. We will use spatial point process methods to define the amount of clustering observed within an image and assess the associated between/within individual variation using a recent extensive collection of blister images. 2. Establish normative ranges for measures of spatial clustering. As a by-product of the first specific aim, we will establish normative ranges for the degree of spatial clustering by body site and diabetes status, stratified by age and sex. 3. Incorporate morphologic measurements. ENF images include information regarding the morphologic structure of the nerve fibers themselves including length, direction, numbers of branches, etc. We propose investigation of statistical models addressing such measures to isolate structural changes in ENFs due to diabetes status. Preliminary results for each aim are promising but require replication on a large number of images to determine their overall utility for screening or as a standard of comparison for assessing performance of other biomarkers. The R21 program structure combined with a recently available collection of blister images provide an ideal mechanism for careful development and critical assessment of spatial analyses of ENF blister images for identifying and verifying progression of neuropathy.